In the field of pathology, there are virtual slide systems which capture and digitize an image of a test sample placed on a prepared slide to enable pathological diagnosis on a display as an alternative to optical microscopes that are pathological diagnostic tools. Digitization of a pathological diagnostic image by a virtual slide system enables a conventional optical microscopic image of a test sample to be handled as digital data. As a result, advantages such as expediting of remote diagnosis, explanation to patients using digital images, sharing of rare cases, and improved efficiency in teaching and learning can be achieved.
In addition, since a wide variety of image processing can be performed on digital data, various diagnosis supporting functions for supporting diagnosis performed by pathologists are being proposed with respect to images captured by virtual slide systems.
Conventionally, the following proposals have been made as examples of diagnosis supporting functions.
Non-Patent Literature 1 discloses a method of extracting cell membrane from a pathologic tissue sample image of a liver using digital image processing technology with an objective to calculate an N/C ratio (a ratio occupied by a nucleus relative to cytoplasm) which is an important finding for diagnosing cancer. In Non-Patent Literature 1, color information of three types of observation images, namely, a bright field observation image, a dark field observation image, and a phase difference observation image is combined to improve a correct extraction rate of cell membrane as compared to using only a bright-field observation image.
In addition, besides a cell membrane, clarifying a cell boundary (in addition to a cell membrane, an intercellular substance (interstice) exists on a cell boundary between cells) and a boundary between a cell and a tube or a cavity is very important when performing diagnoses. Since a clear boundary enables a doctor to more easily estimate a complicated three-dimensional structure of a liver from a sample, a more accurate diagnosis can be achieved from limited information.
Furthermore, the boundary between a cell and a tube or a cavity is also information that is useful for accurately calculating an N/C ratio. For example, since a pathologic tissue sample of a liver may be roughly divided into a region of a cell including a nucleus and cytoplasm and a region of sinusoids that are blood vessels for supplying substances to hepatocyte, the sinusoid region in which a cell does not exist must be correctly eliminated in order to calculate a correct N/C ratio.